Optimize frequent operations

Identify code paths that execute frequently (loops, hot functions, repeated calls) and optimize them by avoiding redundant computations, expensive operations, and unnecessary allocations.

Key optimization strategies:

• Reorder conditions for short-circuiting: Place cheaper or more likely-to-fail conditions first
• Cache expensive computations: Store results of function calls that are used multiple times
• Choose efficient APIs: Prefer operations like fs::rename() over fs::copy() + fs::remove_file()
• Avoid repeated allocations: Use Vec::push() and join() instead of repeated format!() calls
• Reuse objects: Don’t recreate expensive objects like Regex instances in loops

Example of avoiding redundant calls:

// Before: calling node.is_named() twice
fn caller() {
    if node.is_named() {
        render_node_range(cursor, node.is_named()); // redundant call
    }
}

// After: cache the result
fn caller() {
    let is_named = node.is_named();
    if is_named {
        render_node_range(cursor, is_named);
    }
}

Focus especially on optimizing code that processes large datasets, handles user input, or runs in tight loops where small inefficiencies compound into significant performance impacts.